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Dissertation / PhD Thesis/Book | PreJuSER-62599 |
2009
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
Jülich
ISBN: 978-3-89336-569-2
Please use a persistent id in citations: http://hdl.handle.net/2128/3620
Abstract: The currently high cost of fuel cells is determined by expensive materials and low production volume. A detailed understanding of the cost structures reveals unexploited potential that can reduce costs in future. However, this requires a method of predicting costs that can be applied with little effort and which offers both a sufficient degree of detail and also good accuracy. Existing forecasting methods do not, however, fulfil these requirements. The major objective of the present work was to apply mass-specific cost forecasting to fuel cell systems for the first time and to modify the approach for this application. In this method, the cost of an object is estimated solely by means of the object mass with the aid of empirical values (€/kg). The advantages of the method are its simple application and the accuracy of the forecast. Due to the considerable complexity of the fuel cell and the heterogeneity of the materials used, the application of mass-specific cost forecasting does not provide the desired benefits on the level of the aggregated system. The mass-specific cost forecast approach was therefore expanded and optimized. Instead of determining costs on the level of the aggregated system, the cost forecast was applied directly to the individual components. Cost parameters were also embedded in the method in order to include component-internal cost-relevant differences. Due to the great influence of the production rate on the manufacturing costs, an additional dependence on number of units was also integrated. Expanding the empirical values from discrete values to distribution functions enabled a detailed error analysis to be performed and also a statistical localization of the predicted production costs. Empirical values are necessary in order to implement the modified method and therefore an extensive data search was performed. To this end, a methodology was developed which comprehensively described the data acquisition and the required data evaluation on the basis of decision trees. A computer model was created for the mass-specific cost forecast and complemented by a function for assembly costs. The model was successfully applied and validated as part of work on various fuel cell systems. The work showed that the production costs of a fuel cell system can be determined with little effort, good modelling accuracy and high degree of detail by applying modified mass-specific cost forecasting. However, there is a restriction on applications in the light mass range. Apart from the dominant costs of the catalyst and the membrane, system components such as the pumps, compressors, heat exchangers and batteries are responsible for a large proportion of the production costs.
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